This invention generally relates to electrophoresis systems, and more particularly to using an electrophoresis system to determine an integrity of the biomolecules in a sample.
Gene expression analysis is essential to an understanding of molecular processes involved in health and disease. The ability to accurately quantitate steady-state levels of RNA is critical for studying molecular mechanisms of gene expression regulation. RNA quantitation techniques (such as northern blots, DNA microarrays, and real-time quantitative PCR) rely on the use of not only pure, but also intact RNA (i.e. RNA of high integrity). High-throughput gene expression analysis requires rapid, reliable, and standardized evaluation of RNA integrity. Yet, the methods to accurately and objectively evaluate the integrity of RNA molecules, prior to embarking on time-consuming, labor intensive, and costly projects, are limited.
Spectrophotometric methods to evaluate RNA concentrations and purity are well established and widely used. Absorbance at 260 nm (A260) gives an accurate measure of RNA concentration, and the ratio A260/A280 is an accepted indicator of the purity of an RNA preparation with respect to protein or phenol contaminations. However, these methods by themselves may give misleading results because they do not give any information on DNA contamination, the degradation state, or integrity of the sample. While RNA concentration and quality are important parameters for successful downstream applications, RNA integrity is of utmost importance when applications involve RNA quantitation for gene expression studies such as quantitative real-time RT-PCR and cDNA microarrays. Using partially degraded RNA from various states of degradation will lead to varying and incorrect quantitation results, both in microarray experiments and real-time PCR experiments.
The traditional method for assessing the integrity of an RNA sample is by visual inspection after electrophoresis on a formaldehyde agarose gel in the presence of a fluorescent dye (or other luminescent agent), such as ethidium bromide. Observation of two sharp bands, one each for the large and small subunit ribosomal RNAs (rRNAs), with the intensity of the larger band being about twice that of the smaller band, is indicative of intact RNA. While this method is relatively quick and inexpensive, interpretation of the data requires a fair amount of experience, and is still prone to inconsistencies.
Another limitation of this technique using a formaldehyde agarose gel is a requirement of on the order of 200 nanograms (ng) of RNA to make an accurate assessment of its integrity. However, when RNAs are extracted from tissues (such as biopsies) that are available in very limited quantities, agarose gel analysis may not be possible.
A major improvement in RNA analysis occurred with the introduction of microfluidics-based electrophoresis systems that require as little as 100 pg of RNA to produce an electropherogram displaying two distinctive peaks of rRNAs. The digital data composing the electropherogram can be used for a series of computer-based analyses. For example, RNA integrity can be evaluated and quantitated automatically by comparing the area of the peaks corresponding to the rRNAs. In theory, a 28S/18S rRNA ratio close to 2 should be indicative of intact RNA. However, in reality, the rRNA ratio may not be very reliable, e.g., because the peak area measurements are dependent on the chosen start and end points of the peaks.
Because of the limited utility of and reproducibility of rRNA ratios to assess RNA integrity, an existing method (Schroeder et al. US 2006/0246577) attempts to provide a standardized scale for determining RNA integrity. This method obtains a very large number of electropherograms and has trained experts assign a RNA integrity number (RIN). A neural network then determines the features (8 total) of an electropherogram that correspond to certain RIN values. This method can take quite a long time to prepare, e.g., due to the very large number of electropherograms required, the need for evaluation by trained experts, and the computational demands of the neural network. Additionally, this method can provide inaccuracies (inconsistencies) for the researcher, e.g., due to variances in the expert-assigned numbers and varied samples used.
Therefore, it is desirable to have improved methods for determining an integrity of a sample of RNA or other biomolecules.